Interval intuitionistic fuzzy multi-attribute decision making method based on improved entropy and score function
A multi-attribute decision-making, intuition-fuzzy technology, applied in data processing applications, instruments, forecasting, etc., can solve problems such as business and personal economic losses, inability to correctly determine the pros and cons of plans, loss of information, etc.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0078] Example 1, there are 5 candidate suppliers A i (i=1, 2, ..., 5), formulating 6 assessment indicators (attributes) are: service attitude (G 1 ), product quality (G 2 ), technical level (G 3 ), and product price (G 4 ), management system (G 5 ), supply capacity (G 6 ). The attribute weight vector is k=(0.20, 0.10, 0.25, 0.10, 0.15, 0.20) T , and then consulted and recommended by experts, evaluate the 5 candidate suppliers according to the above 6 indicators, and then conduct statistical processing. Assuming that the evaluation information of each supplier under each index is standardized, the interval intuitionistic fuzzy decision matrix is shown in Table 1.
[0079] Table 1 Suppliers' interval information under each assessment index
[0080]
[0081]
[0082] Step 2: Utilize the calculation formula of the improved interval intuitionistic fuzzy entropy in the second step of the present invention to calculate the attribute weight vector as W=(0.064, 0.158, ...
Embodiment 2
[0094] Concepts related to interval intuitionistic fuzzy sets
[0095] 1. Interval intuitionistic fuzzy sets
[0096] Definition 1 Assume that int[0,1] represents the entire closed subset of the interval number [0,1], X is a non-empty set, A={A (x),v A (x)|x∈X>} is an intuitionistic fuzzy set. in,
[0097] mu A : X → Int[0, 1], v A : X → Int[0, 1] (1)
[0098] To meet the conditions
[0099]
[0100] also,
[0101] π A (x)=1-μ A (x)-v A (x) (3)
[0102] Indicates the degree of hesitation that element x in set X belongs to A. π A (x) is also called intuition index or hesitation index, 0≤π A (x)≤1. If π A (x)=0, the intuitionistic fuzzy set degenerates into a fuzzy set. make,
[0103]
[0104]
[0105] but is an interval intuitionistic fuzzy set, then
[0106]
[0107] if and Then interval intuitionistic fuzzy sets degenerate into intuitionistic fuzzy sets.
[0108] 2. Interval intuitionistic fuzzy entropy
[0109] After analyzing the axioma...
Embodiment 3
[0142] Embodiment 3, comparison of interval intuitionistic fuzzy numbers
[0143] For the multi-attribute decision-making problem where the attribute weights are completely unknown, after the weights of each attribute are determined by using the interval fuzzy entropy, the inter-intuitive fuzzy numbers should be sorted. The present invention lists three sorting functions. Let α=([a, b], [c, d]) be an interval intuitionistic fuzzy number.
[0144] 1. Analysis of the limitations of existing scoring functions
[0145] (1) Xu Zeshui defined the scoring function S(α)=(a-c+b-d) / 2 and the exact function h(α)=( a+b+c+d) / 2, the sorting rule is: the larger S(α), the better the interval intuitionistic fuzzy number, and when S(α) is equal, the larger the exact function is, the better the interval intuitionistic fuzzy number is. But for the score function and the exact function, some interval numbers cannot be sorted correctly.
[0146] Example 1α 1 =([0.2,0.3],[0.1,0.4]),α 2 =([0.15,...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com